22__all__ = [
"BaseSelectImagesTask",
"BaseExposureInfo",
"WcsSelectImagesTask",
"PsfWcsSelectImagesTask",
23 "DatabaseSelectImagesConfig",
"BestSeeingSelectVisitsTask",
24 "BestSeeingQuantileSelectVisitsTask"]
28import lsst.utils
as utils
35from lsst.utils.timer
import timeMethod
39 """Base configuration for subclasses of BaseSelectImagesTask that use a
43 host = pexConfig.Field(
44 doc="Database server host name",
47 port = pexConfig.Field(
48 doc=
"Database server port",
51 database = pexConfig.Field(
52 doc=
"Name of database",
55 maxExposures = pexConfig.Field(
56 doc=
"maximum exposures to select; intended for debugging; ignored if None",
63 """Data about a selected exposure.
68 Data ID keys of exposure.
69 coordList : `list` [`lsst.afw.geom.SpherePoint`]
70 ICRS coordinates of the corners of the exposure
71 plus any others items that are desired.
75 super(BaseExposureInfo, self).
__init__(dataId=dataId, coordList=coordList)
79 """Base task for selecting images suitable for coaddition.
82 ConfigClass = pexConfig.Config
83 _DefaultName = "selectImages"
86 def run(self, coordList):
87 """Select images suitable for coaddition in a particular region.
92 List of coordinates defining region of interest;
if `
None`, then
93 select all images subclasses may add additional keyword arguments,
98 result : `pipeBase.Struct`
99 Results
as a struct
with attributes:
102 A list of exposure information objects (subclasses of
103 BaseExposureInfo), which have at least the following fields:
104 - dataId: Data ID dictionary (`dict`).
105 - coordList: ICRS coordinates of the corners of the exposure.
108 raise NotImplementedError()
111def _extractKeyValue(dataList, keys=None):
112 """Extract the keys and values from a list of dataIds.
114 The input dataList is a list of objects that have
'dataId' members.
115 This allows it to be used
for both a list of data references
and a
116 list of ExposureInfo.
131 Raised
if DataId keys are inconsistent.
133 assert len(dataList) > 0
135 keys = sorted(dataList[0].dataId.keys())
138 for data
in dataList:
139 thisKeys = set(data.dataId.keys())
140 if thisKeys != keySet:
141 raise RuntimeError(
"DataId keys inconsistent: %s vs %s" % (keySet, thisKeys))
142 values.append(tuple(data.dataId[k]
for k
in keys))
147 """A container for data to be passed to the WcsSelectImagesTask.
154 Coordinate system definition (wcs).
155 bbox : `lsst.geom.box.Box2I`
156 Integer bounding box for image.
160 super(SelectStruct, self).
__init__(dataRef=dataRef, wcs=wcs, bbox=bbox)
164 """Select images using their Wcs.
167 polygons on the celestial sphere,
and test the polygon of the
168 patch
for overlap
with the polygon of the image.
170 We use
"convexHull" instead of generating a ConvexPolygon
171 directly because the standard
for the inputs to ConvexPolygon
172 are pretty high
and we don
't want to be responsible for reaching them.
175 def run(self, wcsList, bboxList, coordList, dataIds=None, **kwargs):
176 """Return indices of provided lists that meet the selection criteria.
181 Specifying the WCS's of the input ccds to be selected.
183 Specifying the bounding boxes of the input ccds to be selected.
185 ICRS coordinates specifying boundary of the patch.
186 dataIds : iterable [`lsst.daf.butler.dataId`] or `
None`, optional
187 An iterable object of dataIds which point to reference catalogs.
189 Additional keyword arguments.
193 result : `list` [`int`]
194 The indices of selected ccds.
197 dataIds = [
None] * len(wcsList)
198 patchVertices = [coord.getVector()
for coord
in coordList]
201 for i, (imageWcs, imageBox, dataId)
in enumerate(zip(wcsList, bboxList, dataIds)):
203 self.log.info(
"De-selecting exposure %s: Exposure has no WCS.", dataId)
211 """Return corners or `None` if bad.
217 patchPoly : `Unknown`
221 imageCorners = [imageWcs.pixelToSky(pix)
for pix
in geom.Box2D(imageBox).getCorners()]
222 except (pexExceptions.DomainError, pexExceptions.RuntimeError)
as e:
224 self.log.debug(
"WCS error in testing calexp %s (%s): deselecting", dataId, e)
228 if imagePoly
is None:
229 self.log.debug(
"Unable to create polygon from image %s: deselecting", dataId)
232 if patchPoly.intersects(imagePoly):
234 self.log.info(
"Selecting calexp %s", dataId)
241 dimensions=(
"tract",
"patch",
"skymap",
"instrument",
"visit"),
242 defaultTemplates={
"coaddName":
"deep"}):
246class PsfWcsSelectImagesConfig(pipeBase.PipelineTaskConfig,
247 pipelineConnections=PsfWcsSelectImagesConnections):
248 maxEllipResidual = pexConfig.Field(
249 doc=
"Maximum median ellipticity residual",
254 maxSizeScatter = pexConfig.Field(
255 doc=
"Maximum scatter in the size residuals",
259 maxScaledSizeScatter = pexConfig.Field(
260 doc=
"Maximum scatter in the size residuals, scaled by the median size",
265 maxPsfTraceRadiusDelta = pexConfig.Field(
266 doc=
"Maximum delta (max - min) of model PSF trace radius values evaluated on a grid on "
267 "the unmasked detector pixels (pixel).",
275 """Select images using their Wcs and cuts on the PSF properties.
277 The PSF quality criteria are based on the size and ellipticity
278 residuals
from the adaptive second moments of the star
and the PSF.
281 - the median of the ellipticty residuals.
282 - the robust scatter of the size residuals (using the median absolute
284 - the robust scatter of the size residuals scaled by the square of
288 ConfigClass = PsfWcsSelectImagesConfig
289 _DefaultName = "PsfWcsSelectImages"
291 def run(self, wcsList, bboxList, coordList, visitSummary, dataIds=None, **kwargs):
292 """Return indices of provided lists that meet the selection criteria.
297 Specifying the WCS's of the input ccds to be selected.
299 Specifying the bounding boxes of the input ccds to be selected.
301 ICRS coordinates specifying boundary of the patch.
303 containing the PSF shape information for the input ccds to be
305 dataIds : iterable [`lsst.daf.butler.dataId`]
or `
None`, optional
306 An iterable object of dataIds which point to reference catalogs.
308 Additional keyword arguments.
312 goodPsf : `list` [`int`]
313 The indices of selected ccds.
315 goodWcs = super(PsfWcsSelectImagesTask, self).run(wcsList=wcsList, bboxList=bboxList,
316 coordList=coordList, dataIds=dataIds)
320 for i, dataId
in enumerate(dataIds):
323 if self.isValid(visitSummary, dataId[
"detector"]):
328 def isValid(self, visitSummary, detectorId):
329 """Should this ccd be selected based on its PSF shape information.
334 Exposure catalog with per-detector summary information.
343 row = visitSummary.find(detectorId)
346 self.log.warning(
"Removing detector %d because summary stats not available.", detectorId)
349 medianE = np.sqrt(row[
"psfStarDeltaE1Median"]**2. + row[
"psfStarDeltaE2Median"]**2.)
350 scatterSize = row[
"psfStarDeltaSizeScatter"]
351 scaledScatterSize = row[
"psfStarScaledDeltaSizeScatter"]
352 psfTraceRadiusDelta = row[
"psfTraceRadiusDelta"]
355 if self.config.maxEllipResidual
and not (medianE <= self.config.maxEllipResidual):
356 self.log.info(
"Removing visit %d detector %d because median e residual too large: %f vs %f",
357 row[
"visit"], detectorId, medianE, self.config.maxEllipResidual)
359 elif self.config.maxSizeScatter
and not (scatterSize <= self.config.maxSizeScatter):
360 self.log.info(
"Removing visit %d detector %d because size scatter too large: %f vs %f",
361 row[
"visit"], detectorId, scatterSize, self.config.maxSizeScatter)
363 elif self.config.maxScaledSizeScatter
and not (scaledScatterSize <= self.config.maxScaledSizeScatter):
364 self.log.info(
"Removing visit %d detector %d because scaled size scatter too large: %f vs %f",
365 row[
"visit"], detectorId, scaledScatterSize, self.config.maxScaledSizeScatter)
368 self.config.maxPsfTraceRadiusDelta
is not None
369 and not (psfTraceRadiusDelta <= self.config.maxPsfTraceRadiusDelta)
372 "Removing visit %d detector %d because max-min delta of model PSF trace radius values "
373 "across the unmasked detector pixels is not finite or too large: %.3f vs %.3f (pixels)",
374 row[
"visit"], detectorId, psfTraceRadiusDelta, self.config.maxPsfTraceRadiusDelta
381class BestSeeingSelectVisitsConnections(pipeBase.PipelineTaskConnections,
382 dimensions=(
"tract",
"patch",
"skymap",
"band",
"instrument"),
383 defaultTemplates={
"coaddName":
"goodSeeing"}):
384 skyMap = pipeBase.connectionTypes.Input(
385 doc=
"Input definition of geometry/bbox and projection/wcs for coadded exposures",
386 name=BaseSkyMap.SKYMAP_DATASET_TYPE_NAME,
387 storageClass=
"SkyMap",
388 dimensions=(
"skymap",),
390 visitSummaries = pipeBase.connectionTypes.Input(
391 doc=
"Per-visit consolidated exposure metadata",
392 name=
"finalVisitSummary",
393 storageClass=
"ExposureCatalog",
394 dimensions=(
"instrument",
"visit",),
398 goodVisits = pipeBase.connectionTypes.Output(
399 doc=
"Selected visits to be coadded.",
400 name=
"{coaddName}Visits",
401 storageClass=
"StructuredDataDict",
402 dimensions=(
"instrument",
"tract",
"patch",
"skymap",
"band"),
406class BestSeeingSelectVisitsConfig(pipeBase.PipelineTaskConfig,
407 pipelineConnections=BestSeeingSelectVisitsConnections):
408 nVisitsMax = pexConfig.RangeField(
410 doc=
"Maximum number of visits to select",
414 maxPsfFwhm = pexConfig.Field(
416 doc=
"Maximum PSF FWHM (in arcseconds) to select",
420 minPsfFwhm = pexConfig.Field(
422 doc=
"Minimum PSF FWHM (in arcseconds) to select",
426 doConfirmOverlap = pexConfig.Field(
428 doc=
"Do remove visits that do not actually overlap the patch?",
431 minMJD = pexConfig.Field(
433 doc=
"Minimum visit MJD to select",
437 maxMJD = pexConfig.Field(
439 doc=
"Maximum visit MJD to select",
445class BestSeeingSelectVisitsTask(pipeBase.PipelineTask):
446 """Select up to a maximum number of the best-seeing visits.
448 Don't exceed the FWHM range specified by configs min(max)PsfFwhm.
449 This Task is a port of the Gen2 image-selector used
in the AP pipeline:
450 BestSeeingSelectImagesTask. This Task selects full visits based on the
451 average PSF of the entire visit.
454 ConfigClass = BestSeeingSelectVisitsConfig
455 _DefaultName = 'bestSeeingSelectVisits'
457 def runQuantum(self, butlerQC, inputRefs, outputRefs):
458 inputs = butlerQC.get(inputRefs)
459 quantumDataId = butlerQC.quantum.dataId
460 outputs = self.run(**inputs, dataId=quantumDataId)
461 butlerQC.put(outputs, outputRefs)
463 def run(self, visitSummaries, skyMap, dataId):
468 visitSummary : `list` [`lsst.pipe.base.connections.DeferredDatasetRef`]
469 List of `lsst.pipe.base.connections.DeferredDatasetRef` of
471 skyMap : `lsst.skyMap.SkyMap`
472 SkyMap for checking visits overlap patch.
473 dataId : `dict` of dataId keys
474 For retrieving patch info
for checking visits overlap patch.
478 result : `lsst.pipe.base.Struct`
479 Results
as a struct
with attributes:
482 A `dict`
with selected visit ids
as keys,
483 so that it can be be saved
as a StructuredDataDict.
484 StructuredDataList
's are currently limited.
486 if self.config.doConfirmOverlap:
487 patchPolygon = self.makePatchPolygon(skyMap, dataId)
489 inputVisits = [visitSummary.ref.dataId[
'visit']
for visitSummary
in visitSummaries]
492 for visit, visitSummary
in zip(inputVisits, visitSummaries):
494 visitSummary = visitSummary.get()
498 mjd = visitSummary[0].getVisitInfo().getDate().get(system=DateTime.MJD)
500 pixToArcseconds = [vs.getWcs().getPixelScale(vs.getBBox().getCenter()).asArcseconds()
501 for vs
in visitSummary
if vs.getWcs()]
503 psfSigmas = np.array([vs[
'psfSigma']
for vs
in visitSummary
if vs.getWcs()])
504 fwhm = np.nanmean(psfSigmas * pixToArcseconds) * np.sqrt(8.*np.log(2.))
506 if self.config.maxPsfFwhm
and fwhm > self.config.maxPsfFwhm:
508 if self.config.minPsfFwhm
and fwhm < self.config.minPsfFwhm:
510 if self.config.minMJD
and mjd < self.config.minMJD:
511 self.log.debug(
'MJD %f earlier than %.2f; rejecting', mjd, self.config.minMJD)
513 if self.config.maxMJD
and mjd > self.config.maxMJD:
514 self.log.debug(
'MJD %f later than %.2f; rejecting', mjd, self.config.maxMJD)
516 if self.config.doConfirmOverlap
and not self.doesIntersectPolygon(visitSummary, patchPolygon):
519 fwhmSizes.append(fwhm)
522 sortedVisits = [ind
for (_, ind)
in sorted(zip(fwhmSizes, visits))]
523 output = sortedVisits[:self.config.nVisitsMax]
524 self.log.info(
"%d images selected with FWHM range of %d--%d arcseconds",
525 len(output), fwhmSizes[visits.index(output[0])], fwhmSizes[visits.index(output[-1])])
528 goodVisits = {key:
True for key
in output}
529 return pipeBase.Struct(goodVisits=goodVisits)
531 def makePatchPolygon(self, skyMap, dataId):
532 """Return True if sky polygon overlaps visit.
537 Exposure catalog with per-detector geometry.
538 dataId : `dict` of dataId keys
539 For retrieving patch info.
543 result : `lsst.sphgeom.ConvexPolygon.convexHull`
544 Polygon of patch
's outer bbox.
546 wcs = skyMap[dataId['tract']].getWcs()
547 bbox = skyMap[dataId[
'tract']][dataId[
'patch']].getOuterBBox()
552 def doesIntersectPolygon(self, visitSummary, polygon):
553 """Return True if sky polygon overlaps visit.
558 Exposure catalog with per-detector geometry.
559 polygon :` lsst.sphgeom.ConvexPolygon.convexHull`
560 Polygon to check overlap.
564 doesIntersect : `bool`
565 True if the visit overlaps the polygon.
567 doesIntersect = False
568 for detectorSummary
in visitSummary:
569 if (np.all(np.isfinite(detectorSummary[
'raCorners']))
570 and np.all(np.isfinite(detectorSummary[
'decCorners']))):
573 zip(detectorSummary[
'raCorners'], detectorSummary[
'decCorners'])]
575 if detectorPolygon.intersects(polygon):
581class BestSeeingQuantileSelectVisitsConfig(pipeBase.PipelineTaskConfig,
582 pipelineConnections=BestSeeingSelectVisitsConnections):
583 qMin = pexConfig.RangeField(
584 doc=
"Lower bound of quantile range to select. Sorts visits by seeing from narrow to wide, "
585 "and select those in the interquantile range (qMin, qMax). Set qMin to 0 for Best Seeing. "
586 "This config should be changed from zero only for exploratory diffIm testing.",
592 qMax = pexConfig.RangeField(
593 doc=
"Upper bound of quantile range to select. Sorts visits by seeing from narrow to wide, "
594 "and select those in the interquantile range (qMin, qMax). Set qMax to 1 for Worst Seeing.",
600 nVisitsMin = pexConfig.Field(
601 doc=
"At least this number of visits selected and supercedes quantile. For example, if 10 visits "
602 "cover this patch, qMin=0.33, and nVisitsMin=5, the best 5 visits will be selected.",
606 doConfirmOverlap = pexConfig.Field(
608 doc=
"Do remove visits that do not actually overlap the patch?",
611 minMJD = pexConfig.Field(
613 doc=
"Minimum visit MJD to select",
617 maxMJD = pexConfig.Field(
619 doc=
"Maximum visit MJD to select",
625class BestSeeingQuantileSelectVisitsTask(BestSeeingSelectVisitsTask):
626 """Select a quantile of the best-seeing visits.
628 Selects the best (for example, third) full visits based on the average
629 PSF width
in the entire visit. It can also be used
for difference imaging
630 experiments that require templates
with the worst seeing visits.
631 For example, selecting the worst third can be acheived by
632 changing the config parameters qMin to 0.66
and qMax to 1.
634 ConfigClass = BestSeeingQuantileSelectVisitsConfig
635 _DefaultName = 'bestSeeingQuantileSelectVisits'
637 @utils.inheritDoc(BestSeeingSelectVisitsTask)
638 def run(self, visitSummaries, skyMap, dataId):
639 if self.config.doConfirmOverlap:
640 patchPolygon = self.makePatchPolygon(skyMap, dataId)
641 visits = np.array([visitSummary.ref.dataId[
'visit']
for visitSummary
in visitSummaries])
642 radius = np.empty(len(visits))
643 intersects = np.full(len(visits),
True)
644 for i, visitSummary
in enumerate(visitSummaries):
646 visitSummary = visitSummary.get()
648 psfSigma = np.nanmedian([vs[
'psfSigma']
for vs
in visitSummary])
650 if self.config.doConfirmOverlap:
651 intersects[i] = self.doesIntersectPolygon(visitSummary, patchPolygon)
652 if self.config.minMJD
or self.config.maxMJD:
655 mjd = visitSummary[0].getVisitInfo().getDate().get(system=DateTime.MJD)
656 aboveMin = mjd > self.config.minMJD
if self.config.minMJD
else True
657 belowMax = mjd < self.config.maxMJD
if self.config.maxMJD
else True
658 intersects[i] = intersects[i]
and aboveMin
and belowMax
660 sortedVisits = [v
for rad, v
in sorted(zip(radius[intersects], visits[intersects]))]
661 lowerBound = min(int(np.round(self.config.qMin*len(visits[intersects]))),
662 max(0, len(visits[intersects]) - self.config.nVisitsMin))
663 upperBound = max(int(np.round(self.config.qMax*len(visits[intersects]))), self.config.nVisitsMin)
666 goodVisits = {int(visit):
True for visit
in sortedVisits[lowerBound:upperBound]}
667 return pipeBase.Struct(goodVisits=goodVisits)
def __init__(self, dataId, coordList)
def __init__(self, dataRef, wcs, bbox)
def getValidImageCorners(self, imageWcs, imageBox, patchPoly, dataId=None)
static ConvexPolygon convexHull(std::vector< UnitVector3d > const &points)